function Invoke-K8sNodeOrchestration {
    [CmdletBinding()]
    param(
        [ValidateSet('ScaleUp','ScaleDown','Maintenance')]
        [string]$Operation,
        [int]$NodeCount = 1
    )

    $nodePool = Get-AzAksNodePool -ClusterName 'prod-cluster'
    $metrics = Invoke-RestMethod -Uri 'http://k8s-metrics:8080/api/v1/nodes'

    switch ($Operation) {
        'ScaleUp' {
            $newCount = $nodePool.Count + $NodeCount
            Update-AzAksNodePool -Name $nodePool.Name -Count $newCount
            Write-Host "节点池已扩容至$newCount个节点"
        }
        'ScaleDown' {
            $nodesToRemove = $metrics.Nodes | 
                Where-Object { $_.CpuUsage -lt 20 } | 
                Select-Object -First $NodeCount
            $nodesToRemove | ForEach-Object {
                Set-AzAksNode -Name $_.Name -State Draining
            }
        }
        'Maintenance' {
            $metrics.Nodes | Where-Object { $_.HealthStatus -ne 'Healthy' } |
                ForEach-Object {
                    Add-K8sNodeLabel -Node $_.Name -Label @{
                        'maintenance' = (Get-Date).ToString('yyyyMMdd')
                    }
                }
        }
    }
}

function Invoke-AILogAnalysis {
    [CmdletBinding()]
    param(
        [Parameter(Mandatory=$true)]
        [string]$LogPath,
        
        [ValidateSet('Classification','Anomaly')]
        [string]$AnalysisType = 'Classification'
    )

    $analysisReport = [PSCustomObject]@{
        Timestamp = Get-Date -Format 'yyyy-MM-dd HH:mm:ss'
        TotalEntries = 0
        DetectedPatterns = @()
        ModelAccuracy = 0
    }

    try {
        # 加载预训练机器学习模型
        $model = Import-MLModel -Path "$PSScriptRoot/log_analysis_model.zip"

        # 预处理日志数据
        $logData = Get-Content $LogPath | 
            ConvertFrom-LogEntry -ErrorAction Stop |
            Select-Object TimeGenerated, Message, Level

        $analysisReport.TotalEntries = $logData.Count

        # 执行AI分析
        $predictions = switch($AnalysisType) {
            'Classification' {
                $logData | Invoke-MLClassification -Model $model
            }
            'Anomaly' {
                $logData | Invoke-MLAnomalyDetection -Model $model
            }
        }

        # 生成检测报告
        $analysisReport.DetectedPatterns = $predictions | 
            Where-Object { $_.Probability -gt 0.7 } |
            Select-Object LogMessage, PatternType, Probability

        # 计算模型准确率
        $analysisReport.ModelAccuracy = ($predictions.ValidationScore | Measure-Object -Average).Average
    }
    catch {
        Write-Error "日志分析失败: $_"
    }

    # 生成智能分析报告
    $analysisReport | Export-Csv -Path "$env:TEMP/AILogReport_$(Get-Date -Format yyyyMMdd).csv"
    return $analysisReport
}

function Get-AzureCostAnalysis {
    [CmdletBinding()]
    param(
        [Parameter(Mandatory=$true)]
        [string[]]$SubscriptionIds,
        [datetime]$StartDate = (Get-Date).AddDays(-30)
    )

    $report = [PSCustomObject]@{
        Timestamp = Get-Date -Format 'yyyy-MM-dd HH:mm:ss'
        ResourceAnalysis = @()
        CostRecommendations = @()
    }

    foreach ($subId in $SubscriptionIds) {
        Set-AzContext -SubscriptionId $subId | Out-Null
        
        # 获取资源消耗数据
        $resources = Get-AzResource | Where-Object {
            $_.ResourceType -notin @('Microsoft.Resources/deployments','Microsoft.Resources/subscriptions') 
        }

        $resourceGroups = $resources | Group-Object ResourceGroupName
        foreach ($rg in $resourceGroups) {
            $costData = Get-AzConsumptionUsageDetail -StartDate $StartDate -EndDate (Get-Date) -ResourceGroup $rg.Name
            
            $report.ResourceAnalysis += [PSCustomObject]@{
                Subscription = $subId
                ResourceGroup = $rg.Name
                TotalCost = ($costData | Measure-Object PretaxCost -Sum).Sum
                UnderutilizedVMs = $rg.Group.Where{ $_.ResourceType -eq 'Microsoft.Compute/virtualMachines' }.Count
            }
        }
    }

    # 生成优化建议
    $report.ResourceAnalysis | ForEach-Object {
        if ($_.UnderutilizedVMs -gt 5) {
            $report.CostRecommendations += [PSCustomObject]@{
                Recommendation = "调整资源组 $($_.ResourceGroup) 中未充分利用的VM规模"
                PotentialSavings = "预计节省 $([math]::Round($_.TotalCost * 0.3)) 美元"
            }
        }
    }

    $report | Export-Excel -Path "$env:TEMP/AzureCostReport_$(Get-Date -Format yyyyMMdd).xlsx"
    return $report
}

function Invoke-AzureADSecurityAudit {
    param(
        [string]$TenantId,
        [switch]$ExportReport
    )

    try {
        # 连接Azure AD
        Connect-AzureAD -TenantId $TenantId | Out-Null

        # 安全基线检测
        $results = @(
            [PSCustomObject]@{ 
                CheckItem = '多重认证状态'
                Result = (Get-AzureADMSAuthorizationPolicy).DefaultUserRolePermissions.AllowedToCreateApps
            },
            [PSCustomObject]@{
                CheckItem = '旧协议支持状态'
                Result = (Get-AzureADDirectorySetting | Where-Object {$_.DisplayName -eq 'OrganizationProperties'}).Values
            }
        )

        # 生成报告
        if ($ExportReport) {
            $results | Export-Csv -Path "./SecurityAudit_$(Get-Date -Format yyyyMMdd).csv" -NoTypeInformation
        }

        return $results
    }
    catch {
        Write-Error "审计失败：$_"
    }
    finally {
        Disconnect-AzureAD
    }
}

function Get-CloudCostAnalysis {
    [CmdletBinding()]
    param(
        [Parameter(Mandatory=$true)]
        [ValidateSet('Azure','AWS')]
        [string]$CloudProvider
    )

    $threshold = 100 # 美元
    
    switch ($CloudProvider) {
        'Azure' {
            $costData = Get-AzConsumptionUsageDetail -BillingPeriodName (Get-Date).ToString('yyyyMM') |
                Group-Object ResourceGroup |
                Select-Object Name,@{N='Cost';E={$_.Group.PretaxCost | Measure-Object -Sum | Select-Object -Expand Sum}}
        }
        'AWS' {
            $costData = Get-CECostAndUsage -TimePeriod @{Start=(Get-Date).AddDays(-30).ToString('yyyy-MM-dd');End=(Get-Date).ToString('yyyy-MM-dd')} -Granularity MONTHLY |
                Select-Object -Expand ResultsByTime |
                Select-Object -Expand Groups |
                Where-Object {$_.Metrics.UnblendedCost.Amount -gt $threshold}
        }
    }

    $costData | Export-Csv -Path "${CloudProvider}_Cost_Report_$(Get-Date -Format yyyyMMdd).csv" -NoTypeInformation
    
    if ($costData.Count -gt 5) {
        Send-MailMessage -To 'finops@company.com' -Subject "[$CloudProvider] 成本异常警报" -Body "发现${threshold}美元以上资源：$($costData.Count)项"
    }
}

function Invoke-ContainerPipeline {
    [CmdletBinding()]
    param(
        [Parameter(Mandatory=$true)]
        [string]$ImageName,
        [string]$DockerfilePath = './Dockerfile'
    )

    $report = [PSCustomObject]@{
        Timestamp = Get-Date -Format 'yyyy-MM-dd HH:mm:ss'
        BuildLog = @()
        DeploymentStatus = @()
    }

    # 构建Docker镜像
    $buildOutput = docker build -t $ImageName -f $DockerfilePath . 2>&1
    $report.BuildLog += $buildOutput

    # 推送镜像到仓库
    if ($LASTEXITCODE -eq 0) {
        $pushOutput = docker push $ImageName 2>&1
        $report.BuildLog += $pushOutput
    }

    # 部署到Kubernetes
    if ($LASTEXITCODE -eq 0) {
        $k8sOutput = kubectl apply -f deployment.yaml 2>&1
        $report.DeploymentStatus += [PSCustomObject]@{
            Cluster = (kubectl config current-context)
            Status = if($LASTEXITCODE -eq 0){'Success'}else{'Failed'}
            Output = $k8sOutput
        }
    }

    # 生成HTML报告
    $htmlReport = $report | ConvertTo-Html -Fragment
    $htmlReport | Out-File "$env:TEMP/ContainerReport_$(Get-Date -Format yyyyMMdd).html"
    return $report
}

function Invoke-AIOpsAssistant {
    param(
        [Parameter(Mandatory=$true)]
        [string]$Prompt,
        [int]$MaxTokens = 200
    )

    $apiKey = 'sk-xxxxxxxxxxxx'
    $headers = @{
        'Authorization' = "Bearer $apiKey"
        'Content-Type' = 'application/json'
    }

    $body = @{
        model = 'gpt-3.5-turbo'
        messages = @(
            @{
                role = 'system'
                content = '你是一个PowerShell专家，根据用户需求生成可直接运行的脚本。要求：1) 使用原生命令 2) 添加详细注释 3) 包含错误处理'
            },
            @{
                role = 'user'
                content = $Prompt
            }
        )
        max_tokens = $MaxTokens
    } | ConvertTo-Json -Depth 5

    try {
        $response = Invoke-RestMethod -Uri 'https://api.openai.com/v1/chat/completions' \
            -Method Post \
            -Headers $headers \
            -Body $body

        $generatedCode = $response.choices[0].message.content
        $tempScript = [System.IO.Path]::GetTempFileName() + '.ps1'
        $generatedCode | Out-File -FilePath $tempScript
        & $tempScript
    }
    catch {
        Write-Error "AI脚本生成失败：$_"
    }
}

function Optimize-WindowsSystem {
    param(
        [ValidateRange(1,24)]
        [int]$IdleThresholdHours = 4,
        [switch]$CleanTempFiles
    )

    try {
        # 检测闲置服务
        $idleServices = Get-Service | Where-Object {
            $_.Status -eq 'Running' -and 
            (Get-Process -Name $_.Name -ErrorAction SilentlyContinue).StartTime -lt (Get-Date).AddHours(-$IdleThresholdHours)
        }

        # 关闭非核心闲置服务
        $idleServices | Where-Object {$_.DisplayName -notmatch 'Critical'} | Stop-Service -Force

        # 清理临时文件
        if ($CleanTempFiles) {
            $tempPaths = @('$env:TEMP','$env:SystemRoot\Temp','$env:SystemRoot\Prefetch')
            Remove-Item -Path $tempPaths -Recurse -Force -ErrorAction SilentlyContinue
        }

        # 生成优化报告
        [PSCustomObject]@{
            StoppedServices = $idleServices.Count
            TempFilesCleaned = if($CleanTempFiles){ (Get-ChildItem $tempPaths -Recurse | Measure-Object).Count }else{ 0 }
            Timestamp = Get-Date
        } | Export-Clixml -Path "$env:ProgramData\SystemOptimizationReport.xml"
    }
    catch {
        Write-EventLog -LogName Application -Source 'SystemOptimizer' -EntryType Error -EventId 501 -Message $_.Exception.Message
    }
}

function Get-CloudCostReport {
    [CmdletBinding()]
    param(
        [Parameter(Mandatory=$true)]
        [string[]]$SubscriptionIds,
        
        [ValidateSet('Daily','Monthly')]
        [string]$Granularity = 'Monthly'
    )

    $costReport = [PSCustomObject]@{
        Timestamp = Get-Date -Format 'yyyy-MM-dd HH:mm:ss'
        TotalCost = 0
        ServiceBreakdown = @{}
        OptimizationSuggestions = @()
    }

    try {
        # 获取跨云成本数据
        $costData = $SubscriptionIds | ForEach-Object {
            Invoke-RestMethod -Uri "https://management.azure.com/subscriptions/$_/providers/Microsoft.CostManagement/query?api-version=2023-03-01" \
                -Headers @{ Authorization = "Bearer $env:AZURE_TOKEN" } \
                -Body (@{
                    type = "ActualCost"
                    timeframe = "MonthToDate"
                    dataset = @{
                        aggregation = @{
                            totalCost = @{
                                name = "Cost"
                                function = "Sum"
                            }
                        }
                        grouping = @(
                            @{
                                type = "Dimension"
                                name = "ServiceName"
                            }
                        )
                    }
                } | ConvertTo-Json)
        }

        # 分析成本结构
        $costReport.TotalCost = ($costData.properties.rows | Measure-Object -Property [0] -Sum).Sum
        $costReport.ServiceBreakdown = $costData.properties.rows | 
            Group-Object { $_[1] } -AsHashTable | 
            ForEach-Object { @{$_.Key = [math]::Round($_.Value[0],2)} }

        # 生成优化建议
        $costData.properties.rows | Where-Object { $_[0] -gt 1000 } | ForEach-Object {
            $costReport.OptimizationSuggestions += [PSCustomObject]@{
                Service = $_[1]
                Cost = $_[0]
                Recommendation = "考虑预留实例或自动缩放配置"
            }
        }
    }
    catch {
        Write-Error "成本数据获取失败: $_"
    }

    # 生成Excel格式报告
    $costReport | Export-Excel -Path "$env:TEMP/CloudCostReport_$(Get-Date -Format yyyyMMdd).xlsx"
    return $costReport
}

function Invoke-AIOpsAutomation {
    [CmdletBinding()]
    param(
        [Parameter(Mandatory=$true)]
        [string]$OperationContext,
        
        [ValidateRange(1,100)]
        [int]$MaxTokens = 60
    )

    $apiKey = $env:OPENAI_API_KEY
    $prompt = @"
作为资深PowerShell运维专家，请根据以下运维场景生成可执行的解决方案：
场景：$OperationContext
要求：
1. 使用标准PowerShell命令
2. 包含错误处理机制
3. 输出结构化数据
4. 确保跨平台兼容性
"@

    $body = @{
        model = "gpt-3.5-turbo"
        messages = @(@{role="user"; content=$prompt})
        max_tokens = $MaxTokens
    } | ConvertTo-Json

    $response = Invoke-RestMethod -Uri 'https://api.openai.com/v1/chat/completions' \
        -Method Post \
        -Headers @{ Authorization = "Bearer $apiKey" } \
        -ContentType 'application/json' \
        -Body $body

    $codeBlock = $response.choices[0].message.content -replace '```powershell','' -replace '```',''
    [scriptblock]::Create($codeBlock).Invoke()
}